Research Papers

Mapping Cyclist Activity and Injury Risk in a Network Combining Smartphone GPS Data and Bicycle Counts

Filename 1A-Strauss-FP-Student.pdf
Filesize 2 MB
Version 1
Date added June 18, 2015
Downloaded 10 times/fois
Category 2015 CARSP XXV Ottawa
Tags Research and Evaluation, Session 1A, Student Paper Award Winner
Author/Auteur Jillian Strauss, Ph.D. (Candidate), Luis F. Miranda-Moreno, Ph.D., Patrick Morency
Stream/Volet Research and Evaluation
Award/Prix Étudiant 2 Student

Slidedeck Presentation

1A - .Strauss

Abstract

In recent years, research has been carried to identify environmental risk factors and map injury
risk for cyclists. These tasks require three main sources of data: geocoded injury data, geometric
design and built environment characteristics as well as exposure measures, also referred to as
motor-vehicle and bicycle flows, volumes or activity. Bicycle flow data on each facility and
network element is an essential component in the calculation of cyclist injury rates (also referred
to as risk). Bicycle flows are required to identify routes and corridors with high injury risk or with
high bicycle activity. This knowledge will serve as vital information for cities wishing to implement
appropriate cycling infrastructure. The main objectives of this study are to estimate and map
bicycle volumes, injuries and risk throughout the entire network of road segments and
intersections on the island of Montreal, combining smartphone GPS traces and cyclist counts
(manual and automatic, short-term (hours) and long-term (months and years)) to then validate
the use of GPS data as a potential source of cyclist exposure data. Bayesian methods are
applied to the GPS data to map cyclist injuries and risk throughout the entire island of Montreal.
Among other results, cyclist risk is greatest outside the central neighbourhoods and where
bicycle infrastructure is not present and much greater at intersections than along segments. This
study validates the use of GPS data as a new and reliable source of bicycle flow estimation,
useful in a variety of safety analyses carried out at the entire urban network level.

Jillian Strauss, Ph.D. (Candidate), Luis F. Miranda-Moreno, Ph.D., Patrick Morency